KDD
Govern AI agents with deterministic gates. No LLM judging.
8 followers
Govern AI agents with deterministic gates. No LLM judging.
8 followers
KDD is a template repo + method to govern AI coding agents. Write a contract, seal its tests by SHA256, and let 12 deterministic gates (pure Python stdlib, no LLM, no network) verify — so the agent that implements never judges "done."
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Tines The single, secure environment for agents, apps, and automations.
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Would love to see a built-in dry-run mode that shows which of the 12 gates would fail on the current contract before any agent touches the code. Would make onboarding way smoother for teams adopting KDD and help catch weak test seals early.
@seraptc6r This is a great catch, Serap. You’re right—right now the 'engine' is there, but the 'mouth' (the CLI) is missing, and that's a hurdle for onboarding.
I’ve been looking into a preflight command that runs exactly what you described: validation for the current contract, coverage for all 12 gates (including the local-only ones), and a nice CLI summary. I’m also weighing adding a 'weak seal' advisory mode as a follow-up.
It's definitely moving to the top of the roadmap. I'd love to loop you in when the first preflight prototype is ready if you're interested in testing it!
@seraptc6r Shipped: scripts/preflight.py. Full mode runs all 12 gates locally against the current repo and reports which would fail — before any agent touches the code:
There's also a --contract <task> mode that scopes it to 3 checks on a single task contract (frontmatter, oracle seal, test_command) — useful when you're only touching one contract and don't want the full sweep. Contract: knowledge/contracts/preflight.md. Came directly out of this thread — thanks for pushing on it.
the sha256 sealed tests is honestly such a clean move, basically removes any wiggle room for the agent to rationalize its own work. love that it's pure stdlib too, no extra dependencies to babysit.
@filizlhzb Thanks, Filiz! That's exactly the design goal, the hash doesn't care how convincing the rationalization is, it just doesn't match. And yeah, stdlib-only was non-negotiable for me: the whole point is a verification path an agent (or a supply-chain attack) can't quietly influence by pulling in a new dependency.
@filizlhzb Also shipped, closing the loop on "weak-seal advisory": scripts/audit_seals.py. It flags frozen oracles that the seal certifies as intact but that can't actually fail — assert True, no test functions, or a test file that never references the target at all. Advisory by design (warnings, exit 0) so it doesn't become a second gate; --strict if your team wants to enforce it. Contract: knowledge/contracts/seal-audit.md.
Pinned the SHA sealed tests idea straight away, that is exactly the missing piece in every AI agent loop I've seen. twelve deterministic gates run locally without the model second guessing itself feels like the right amount of guardrail. Going to wire it into our internal tooling this week.
@zelihaireltxnu Thanks for the pin, Zeliha! That’s exactly why I built it—I got tired of seeing agents rewrite their own evaluation criteria to fake a 'success' state.
I'd love to hear how the integration goes with your internal tools this week. Please feel free to tear it apart and drop any feedback, edge cases, or friction points you run into. Super curious to know if the contract-first approach feels smooth for your team!